Taking handheld photos in low-light conditions is challenging. Since less light is available, longer exposure times are needed to obtain an adequately exposed image. A consequence of longer exposure times is that the quality of the photo is more susceptible to camera movement which, in turn, results in a blurred image. In order to avoid camera movement, photographers frequently use a tripod to support a camera. However, use of a tripod to remove movement is not always practical. This is particularly relevant with the proliferation of mobile phones with built-in cameras. Consequently, in many, if not almost all circumstances, camera shake is likely to be an issue resulting in blurry pictures.
Blur may be removed, with varying degrees of success, from a blurred image in an attempt to recover a latent sharp image. Known techniques utilize a user defined blur kernel to deblur an entire image using deconvolution. One of the most critical parameters in the deblurring process is the size of the blur kernel. Most existing methods require blur kernel size as an input parameter, and deblurring performance is often sensitive to the kernel size. Blur kernel size set too small or too large relative to the blurred region would result in an incorrectly estimated kernel size, and would not adequately restore a sharp image from a blurred image. Further, the dimensionality of the solution space increases and deblurring is more computationally intensive.
It will thus be appreciated that it is extremely challenging for casual users without trained eyes to specify the kernel size correctly. Thus, deblurring can become a frustrating process for users trying several different values to figure out the right blur kernel size. Accordingly, providing assistance to a user in selecting the size of a blur kernel to deblur an image would be very beneficial.